1. Field of the Invention
The present invention generally relates to an apparatus and method for determining a search set for resource allocation in a multi-antenna system, and more particularly to an apparatus and method for generating a reduced search set to be used to determine a data transmission rate to be allocated to each antenna.
2. Description of the Related Art
Wireless mobile communication markets are rapidly growing. Various multimedia services are required in wireless environments. Efforts are in progress to provide high-speed, large-capacity data transmission. For this, the most urgent problem is to find a method for efficient use of limited frequency. To address this problem, a new transmission technology using multiple antennas is required.
As a representative example of the new transmission technology using the multiple antennas, a multiple-input multiple-output (MIMO) system has been proposed. The MIMO system requires an efficient signal processing algorithm for providing a high-quality data service at a high transmission rate.
An example of the signal-processing algorithm is a resource allocation algorithm. The resource allocation algorithm allocates resources, that is, data transmission rates, on an antenna-by-antenna basis to achieve a target error rate while minimizing resource consumption. The resource allocation algorithm may be divided into signal processing algorithms at a transmitting side and a receiving side. When the data transmission rates are allocated on the antenna-by-antenna basis, the transmitting side finds resource allocation in which the target error rate can be achieved while minimizing energy consumption.
Existing resource allocation algorithms are uniform allocation, fixed allocation and full-search allocation.
The uniform allocation scheme allocates the same data transmission rate on an antenna-by-antenna basis. This is the simplest resource allocation scheme in which feedback information transmission is unnecessary. However, there is a disadvantage in that performance is inferior since the error rate is high even when Successive Interference Cancellation (SIC) as well as linear detection is used.
The fixed allocation scheme designates optimal allocation and uses the designated allocation for all channels. The optimal allocation is determined by channel statistics. If the channel statistics are useful, the fixed allocation scheme outperforms the uniform allocation scheme. However, error rate performance may be limited since allocation is fixed and also the fixed allocation does not stably operate under varied channel conditions.
The full-search allocation scheme uses all available combinations as candidates for data transmission rate allocation. Among the candidates, a candidate requiring the lowest power is used for allocation to a current channel. This scheme exhibits the best performance since all cases are considered. However, the full-search allocation scheme is disadvantageous in that complexity and feedback information increase. To reduce the complexity in the full-search allocation scheme, an iterative algorithm has been proposed.
The signal-processing algorithm at the receiving side detects the channel's state of each transmission channel and feeds back the detection result to the transmitting side. On the basis of the detection result fed back from the receiving side, the signal processing algorithm at the transmitting side allocates resources on a transmit (Tx) antenna-by-Tx antenna basis.
The Bell Labs Layered Space Time (BLAST) technology is a representative example of the signal-processing algorithm. The BLAST technology may increase a data transmission amount using multiple antennas without increasing the frequency domain to be used by a system.
This BLAST technology is divided into diagonal-BLAST (D-BLAST) and vertical-BLAST. D-BLAST may achieve high spectral efficiency using specified block coding between data to be transmitted from Tx antennas for a diagonal transmission, but has the drawback in that implementation complexity is high. However, V-BLAST may reduce the complexity by independently transmitting data from the Tx antennas.
Moreover, the signal-processing algorithm at the receiving side is used to detect signals transmitted from Tx antennas using received signals. The signal-processing algorithm at the receiving side may be divided into a linear detection scheme and a non-linear detection scheme.
The Zero Forcing (ZF) technique and Minimum Mean Square Error (MMSE) technique are examples of the linear detection scheme.
The ZF technique eliminates intersymbol interference by computing criteria with respect to column vectors, detecting a signal component from a symbol mapped to a column vector with largest magnitude and eliminating the detected signal component from a received signal. The MMSE technique minimizes the mean square error between the original transmitted symbols and estimated signals at the receiving side.
The Maximum Likelihood (ML) detection technique and the SIC technique are examples of the non-linear detection scheme.
The ML technique may significantly improve performance by selecting an input with a minimum squared Euclidean distance using all possible transmitted symbols from Tx antennas. However, complexity may exponentially increase according to the number of Tx antennas and modulation order. The ML technique exhibits the best performance, but has a drawback in that implementation is complex due to an increase in the computation amount.
The SIC technique is an interference cancellation technique for improving performance by first detecting and eliminating a channel with a high Signal to Interference plus Noise Ratio (SINR). The SIC technique additionally requires ordering to achieve the best performance.
For performance improvement of the MIMO system as described above, improved signal detection and resource allocation methods are required which can correctly detect a transmitted signal from a received signal and can avoid the increase in computation amount.